Skip to content

Commit

Permalink
Update common.py lists for tuples (ultralytics#7063)
Browse files Browse the repository at this point in the history
Improved profiling.
  • Loading branch information
glenn-jocher authored Mar 20, 2022
1 parent f692e07 commit 09ddede
Showing 1 changed file with 5 additions and 5 deletions.
10 changes: 5 additions & 5 deletions models/common.py
Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@
def autopad(k, p=None): # kernel, padding
# Pad to 'same'
if p is None:
p = k // 2 if isinstance(k, int) else [x // 2 for x in k] # auto-pad
p = k // 2 if isinstance(k, int) else (x // 2 for x in k) # auto-pad
return p


Expand Down Expand Up @@ -133,7 +133,7 @@ def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5): # ch_in, ch_out, nu
self.cv2 = Conv(c1, c_, 1, 1)
self.cv3 = Conv(2 * c_, c2, 1) # act=FReLU(c2)
self.m = nn.Sequential(*(Bottleneck(c_, c_, shortcut, g, e=1.0) for _ in range(n)))
# self.m = nn.Sequential(*[CrossConv(c_, c_, 3, 1, g, 1.0, shortcut) for _ in range(n)])
# self.m = nn.Sequential(*(CrossConv(c_, c_, 3, 1, g, 1.0, shortcut) for _ in range(n)))

def forward(self, x):
return self.cv3(torch.cat((self.m(self.cv1(x)), self.cv2(x)), dim=1))
Expand Down Expand Up @@ -194,7 +194,7 @@ def forward(self, x):
warnings.simplefilter('ignore') # suppress torch 1.9.0 max_pool2d() warning
y1 = self.m(x)
y2 = self.m(y1)
return self.cv2(torch.cat([x, y1, y2, self.m(y2)], 1))
return self.cv2(torch.cat((x, y1, y2, self.m(y2)), 1))


class Focus(nn.Module):
Expand All @@ -205,7 +205,7 @@ def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True): # ch_in, ch_out, k
# self.contract = Contract(gain=2)

def forward(self, x): # x(b,c,w,h) -> y(b,4c,w/2,h/2)
return self.conv(torch.cat([x[..., ::2, ::2], x[..., 1::2, ::2], x[..., ::2, 1::2], x[..., 1::2, 1::2]], 1))
return self.conv(torch.cat((x[..., ::2, ::2], x[..., 1::2, ::2], x[..., ::2, 1::2], x[..., 1::2, 1::2]), 1))
# return self.conv(self.contract(x))


Expand All @@ -219,7 +219,7 @@ def __init__(self, c1, c2, k=1, s=1, g=1, act=True): # ch_in, ch_out, kernel, s

def forward(self, x):
y = self.cv1(x)
return torch.cat([y, self.cv2(y)], 1)
return torch.cat((y, self.cv2(y)), 1)


class GhostBottleneck(nn.Module):
Expand Down

0 comments on commit 09ddede

Please sign in to comment.